Discovering users` access patterns for web usage mining from web log files

Abstract

Web Usage Mining (WUM) is the automatic discovering of hidden information of user access pattern from the web log data. Frequent pattern discovery is one of the main techniques in WUM that can be used to implement recommender systems, forecast user`s navigational behaviour, and personalize web sites. Many algorithms have been suggested on obtaining frequent user navigation patterns. This paper presents PD-FARM (Pattern Discovery based on Fuzzy Association Rule Mining) algorithm to extract the web usage patterns, based on Fuzzy Association Rule Mining (FARM). Fuzzy Frequent Pattern-Growth (FFP-Growth) algorithm is used to FARM. Finally, an illustrated example is given for complete description of the proposed algorithm.